Update README.md

README.md

@@ -82,16 +82,6 @@ ChingMu 1000H is an optical motion capture dataset designed for training and val
 | Semantic labels / 语义标签 | `.jsonl` | Task, scenario, action, object |
 
 
-## 📸 Sample Visualization / 样本可视化
-
-Display is a snapshot from our motion capture studio showing a subject performing a box-moving task, with real-time skeleton overlay and object tracking:  
-以下是我们动捕棚的截图，展示了一名受试者执行搬箱子任务的过程，包含实时骨骼叠加和物体追踪：
-
-<img src="https://github.com/ChingmuData/CMRD/raw/refs/heads/main/assets/logo.png"></img>
-
-*Figure: Optical mocap data visualized with skeleton and tracked object.*  
-*图：光学动捕数据可视化，显示骨骼和追踪物体。*
-
 ## 🎥 Preview Video / 预览视频
 
 Watch a short demonstration of the motion capture data in action:  
@@ -117,31 +107,6 @@ Watch a short demonstration of the motion capture data in action:
 - 虚拟制作与动画参考
 
 
----
-
-## Task & Scenario Taxonomy / 任务与场景分类
-
-All takes are indexed in `metadata/index.csv`. Key filter columns:  
-所有数据片段均在 `metadata/index.csv` 中索引。关键筛选列：
-
-| Column / 列名 | Values / 取值 | Use / 用途 |
-|---|---|---|
-| `scenario` | `industrial`, `household`, `retail`, `healthcare`, `logistics`, `agri`, `performance` | Filter by scene / 按场景筛选 |
-| `task_category` | `locomotion`, `manipulation`, `dexterous_hand`, `tool_use`, `interaction` | Broad category / 大类 |
-| `task_label` | `walk_carrying_box`, `screw_with_driver`, `pinch_grasp_bottle` … | Specific task / 具体任务 |
-| `has_finger_data` | `true` / `false` | Needs hand DoF? / 是否需要手指数据 |
-| `has_object_6d` | `true` / `false` | Needs object tracking? / 是否需要物体追踪 |
-| `quality_flag` | `pass` / `warning` / `fail` | Skip bad takes / 跳过低质量数据 |
-| `retarget_available` | `g1` / `none` | Robot format / 机器人格式 |
-
-Full taxonomy includes locomotion, manipulation, dexterous hand, tool use, object interaction, social contact, and performance.  
-完整分类包括：移动、操作、灵巧手、工具使用、物体交互、社交接触和表演。
-
-
-> 👀 Try the interactive **Dataset Preview** at the top of this page (select `metadata` config) or download [`metadata/index.csv`](https://huggingface.co/datasets/ZIHLING/Chingmu-RobotData/resolve/main/metadata/index.csv) for offline filtering.  
-> 👀 尝试页面顶部的交互式**数据集预览**（选择 `metadata` 配置），或下载 `metadata/index.csv` 进行离线筛选。
-
-
 ---
 
 ### Full Taxonomy (abridged) / 完整分类（简版）
@@ -226,8 +191,8 @@ For full access, request permission via the **Request access** button, then use
 **Accuracy:** joint error <1mm, object pose ±2mm / ±0.5°, temporal sync <1 frame.  
 **精度：关节误差 <1mm，物体位姿 ±2mm / ±0.5°，时间同步 <1 帧。**
 
-**Limitations:** performer age skew (20–35), finger precision depends on calibration, object accuracy varies with marker cluster size.  
-**局限：表演者年龄偏向（20-35岁），手指精度取决于校准，物体精度随标记簇大小变化。**
+**Limitations:** performer age skew (20–35), object accuracy varies with marker cluster size.  
+**局限：表演者年龄偏向（20-35岁），物体精度随标记簇大小变化。**
 
 **Ethics:** all performers consented; faces excluded from skeleton data; no biometric identifiers retained.  
 **伦理：所有表演者已签署同意书；面部未包含在骨骼数据中；未保留生物特征标识。**